Using NHDPlus as the Land Base for the Noah-distributed Model

122570989…from Transactions in GIS

“The National Elevation, Hydrography and Land Cover datasets of the United States have been synthesized into a geospatial dataset called NHDPlus which is referenced to a spheroidal Earth, provides geospatial data layers for topography on 30 m rasters, and has vector coverages for catchments and river reaches. In this article, we examine the integration of NHDPlus with the Noah-distributed model. In order to retain compatibility with atmospheric models, Noah-distributed utilizes surface domain fields referenced to a spherical rather than spheroidal Earth in its computation of vertical land surface/atmosphere water and energy budgets (at coarse resolution) as well as horizontal cell-to-cell water routing across the land surface and through the shallow subsurface (at fine resolution). Two data-centric issues affecting the linkage between Noah-distributed and NHDPlus are examined: (1) the shape of the Earth; and (2) the linking of gridded landscape with a vector representation of the stream and river network. At mid-latitudes the errors due to projections between spherical and spheroidal representations of the Earth are significant. A catchment-based “pour point” technique is developed to link the raster and vector data to provide lateral inflow from the landscape to a one-dimensional river model. We conclude that, when Noah-distributed is run uncoupled to an atmospheric model, it is advantageous to implement Noah-distributed at the native spatial scale of the digital elevation data and the spheroidal Earth of the NHDPlus dataset rather than transforming the NHDPlus dataset to fit the coarser resolution and spherical Earth shape of the Noah-distributed model.”

Cartographic Representation of the Sonic Environment

caj…from The Cartographic Journal

“The description of the landscape is based on the visualization of geographic features and the representation of their attributes. Although sound is a major component of any environment, its cartographic representation is limited mainly on noise mapping and in urban or sub-urban areas. Soundscape is a term that describes the acoustic relation between the environment and the individual in a landscape context, considering all kinds of interactions between space, sound and humans. The representation of the soundscape at a spatial level would support many applications such as geographic analysis, ecosystem evaluation, environmental education, landscape management, urban or rural planning and protection of sonic particularities. This paper proposes a methodology for the mapping of both quantitative and qualitative attributes of a rural soundscape, which is described through the study of the acoustic environment around a protected wetland in Greece.”

Modeling Geographic Complexity: Special Session at Association of American Geographers Annual Meeting, April 2010

aagAssociation of American Geographers Annual Meeting
April 14-18, 2010, Washington, DC, USA

Understanding geographical systems represents one of the greatest challenges of our time. Complexity has emerged as a useful paradigm to effectively study linked human, socioeconomic and biophysical systems at a variety of different spatial and temporal scales. As a result, descriptive and predictive models of various levels of sophistication and using mostly agents, genetic algorithms, cellular automata and neural networks are now beginning to regularly appear in the geographic literature. However, there still remains many unresolved conceptual, technical and application challenges associated with these complexity based models. The goal of this session is to focus on the following themes:

  1. Conceptual: shared and unique complexity signatures in geographic systems; existing and emerging geographical and complexity theories; epistemological and ontological influences; complexity based model designs; networks and hybrid models; linking classical and spatial statistics in complexity studies.
  2. Technical: space-time patterns and dynamics; standardizing the development and representation of complex systems; rule selection and implementation; multiple-scale interactions and structure, system evolution and self-organization; learning and adaptation; calibration, validation and verification; path-dependence; non-linearity.
  3. Applications: effectiveness of complexity models when embedded in political, institutional and socio-economic systems; human-environment interactions; earth systems science; land use science; landscape ecology; sustainability analysis.

In order to widely disseminate the ideas emerging from this session, the organizers of the session are exploring the possibility for a special issue of a journal and /or an edited book so that authors will have the opportunity to suitably revise their presentations for publication. Priority will be given for work that has not been published, in review or in press.

Please e-mail the abstract and key words with your expression of intent to Andrew Crooks <acrooks2@gmu.edu> by October 19th, 2009.